1. Field of the Invention
The present invention relates to a system and method suitable for remote selection and delivery of customized contents such as advertisements, and particular to a system and method used to increase web advertisement response rates by providing customized advertisements shown as inline images and banners in web pages.
2. Description of the Related Arts
Nowadays, the Internet is very popular with the consuming public and WWW (World Wide Web) pages on the Internet are considered powerful media for advertising. In its simplest form, web advertisement is directly linked as fixed inline images into a web page. More flexible systems allow a separation of advertisement selection and placement, but offer only a random selection mechanism. This is possible since web documents do not contain images directly, but carry only a reference to the image itself. By having this reference not point to an actual image, but to an automated selection process, such a referenced inline image can be selected as late as the time the actual layout of the page is being made in the user""s browser window. Moreover, each user who requests the page for display will potentially see a different inline image since the selection process is called for each user individually.
As an extension to this basic mechanism, many systems in use today (such as AdForce by AdForce, Inc. or AdKnowledge by AdKnowledge, Inc.) allow advertisers to specify targeting constrains that limit the display of an advertisement banner to certain conditions, such as the type of browser software used or the time of the day. Such a system first filters out all non-applicable advertisements given the condition of the current request for a banner. The remaining advertisements will then be selected randomly. Typical features include: type and version of browser software, operating system (OS), site originating the request, country, time of day, day of week. Several systems increasingly attempt to link such connection specific information to user specific data such as age, gender, income, place of residence, etc.
Japanese Patent Laid-Open Application No. 134371/97 (JP, 09134371, A) discloses an information retrieve system in which a search engine server and an advertisement server are provided independently on the Internet and, when a user issues a query to the search engine server through a client terminal, the advertisement server sends advertisement information relevant to the query to the client terminal.
Japanese Patent Laid-Open Application No. 240828/98 (JP; 10240828, A) discloses an advertisement distribution service system in which a CD-ROM (compact disc read only memory) including various advertisements is distributed to each user, dynamic log data of the user access is recorded by a center system, and an advertisement selected by the center system based on the dynamic log data is read from the CD-ROM and displayed on a terminal screen of the corresponding user.
Latest versions of advertisement selection systems (such as DART by DoubleClick, Inc.) offer simple click-boost mechanisms that, on top of the feature filtering mechanisms described above, keep statistics on how well each advertisement performed under the present conditions. Once a pool of available advertisements has been filtered out, the advertisement with the highest click-through will be selected. Others identify each user using a xe2x80x9ccookiexe2x80x9d (See Kristol, D. and Montulli, L. RFC2109: HTTP state management mechanism. Network Working Group, IETF, February 1997) (RFC=Request for Comments, and IETF=Internet Engineering Task Force) and limit the amount of times the same advertisement is shown to prevent xe2x80x9cbanner wearoutxe2x80x9d. A cookie is a short piece of information, typically a user ID, that is sent by the server together with the requested page or image. The user""s browser will store this information and resubmit it whenever the user requests a page or an image from the same server.
Finally, a few systems (such as the Accipiter AdManager from Engage or SelectCase for Ad Servers from Aptex, Inc.) combine neural network technologies (as described by Caid, W. et al. in U.S. Pat. No. 5,619,709, System and Method of context vector generation and retrieval. Apr. 8, 1997) with individual user identification to create fully personalized advertisement placement, observing every single web page a user requests and thus accumulating an online interest dossier on each user.
Many of the methods described above are too simple to take advantage of the just-in-time selection and delivery process of Web advertisement. Filtering techniques allow for a very precise targeting, but leave the task of selecting whom to target what advertisement to largely to the advertiser. This requires extended efforts on the advertiser side, who has to rely on countless statistics and demographic studies.
Although personalized advertisement delivery seems to solve this problem, the high amount of user monitoring clashes with an individuals need for privacy. Moreover, such intrusive techniques have not yet been proved to be effective in boosting click-through rates. However, one of the largest drawback of such systems using neural network technology is their inability to take display constraints, such as the minimum number of impressions to be shown for each advertisement, into account when selecting the best matching advertisement.
An objective of the present invention is improving the system for providing customized advertisement selection and delivery on the network.
Another objective of the present invention is improving the method for providing customized advertisement selection and delivery on the network.
The first objective of the invention is achieved by an apparatus which provides electronic advertisement to a client system coupled to the apparatus, the apparatus comprising: a database which stores advertisements and their campaign information; an advertisement server which generates electronic advertisement available to the client system; and means for performing a customization process which customizes the electronic advertisements to be delivered to each client system.
The other objective of the present invention is achieved by a method of providing electronic advertisements to a client system, the method comprising the steps of decoding customization parameters embedded in a request from the client system, querying a database for a list of display probabilities for relevant values of the customization parameters, computing an overall display probability for the overall request, and selecting an advertisement according to the display probability.
The other objective of the present invention is also achieved by a method for querying a database for a list of display probabilities for relevant values of given customization parameters, the method comprising steps of: providing a learning system which pre-computes the display probabilities; and periodically updating display probabilities by the learning system.
The present invention is directed to a system serving customized advertisements on-demand over the Hypertext Transfer Protocol (HTTP). A user connects to the system indirectly by downloading a content page from a publisher which contains a reference to an inline image. This image is then requested by the browser, transparent to the user, directly from the system described here. The system uses a pre-computed, periodically updated table of display probabilities which prescribe a distribution for the available advertisements given the current conditions. By making a choice according to the obtained distribution the system will return a customized banner advertisement to the user""s browser.
The overall system architecture according to the present invention allows distributed advertisement delivery. All components can either be at a single centralized location or on different machines and in different places. Although cookies can be used to help session identification, they are not necessary for operation. Most importantly, the system is able to automatically adapt to usage pattern. Advertisers simply have to register their advertisement with the system and can leave advertisement targeting to the automated learning system. However, the advertiser remains in full control by being able to specify an arbitrary number of display constraints. The system will attempt to maximize the click-through for each single advertisement by relying on past experience. Performance can further be increased by grouping related advertisements into families and selecting among families instead of single advertisements.
The above and other objects, features, and advantages of the present invention will be apparent from the following description referring to the accompanying drawings which illustrate an example of a preferred embodiment of the present invention.